Dependency Packages
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AtomGraphs.jl12Graph-building for AtomicGraphNets
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TextEncodeBase.jl12Text preprocessing library with framework for composable tokenizations
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ActionModels.jl11A Julia package for behavioural modeling
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KitML.jl11Lightweight module of neural differential equations in Kinetic.jl
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JutulDarcyRules.jl11JutulDarcyRules: ChainRules extension to Jutul and JutulDarcy
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Sisyphus.jl11A high-performance library for gradient based quantum optimal control
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Jello.jl10-
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OperatorFlux.jl10Operator layers for Flux.jl that allow for the construction of Neural Operator models by using Flux's API. Useful for discretization-independent spatio-temporal ML models.
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EvoLinear.jl10Linear models
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DiffRaster2D.jl10Differentiable 2d rasterizer in Julia
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DynamicOED.jl10Optimal experimental design of ODE and DAE systems in julia
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ExpressionTreeForge.jl10-
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MLJIteration.jl10A package for wrapping iterative MLJ models in a control strategy
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ParametrisedConvexApproximators.jl9A Julia package for parameterized convex approximators including parameterized log-sum-exp (PLSE) network.
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LearningHorse.jl9LearningHorse.jl is the ML library for JuliaLang.
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CTDirect.jl9Direct transcription of an optimal control problem and resolution
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HorseML.jl9HorseML.jl is the ML library for JuliaLang.
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SpinGlassPEPS.jl9-
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MLJJLBoost.jl9MLJ.jl interface for JLBoost.jl
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PartiallySeparableNLPModels.jl9A three-way bridge between ExpressionTreeForge.jl, PartitionedStructures.jl and PartiallySeparableSolvers.jl
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JLBoostMLJ.jl9MLJ.jl interface for JLBoost.jl
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RNAForecaster.jl8-
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StatisticalMeasuresBase.jl8A Julia package for building production-ready measures (metrics) for statistics and machine learning
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KnetNLPModels.jl8An NLPModels Interface to Knet
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PartiallySeparableSolvers.jl8Trust-region methods with partitioned quasi-Newton approximations
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ShipMMG.jl8Ship maneuvering simulation tool with respect to ShipMMG model
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MLJFlow.jl8Connecting MLJ and MLFlow
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LuxLib.jl7Backend for Lux.jl
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GraphNetCore.jl7GraphNetCore.jl is a software package for the Julia programming language that provides an the core functionality of the MeshGraphNets.jl package. Some parts are based on the implementation of the MeshGraphNets framework by Google DeepMind for simulating mesh-based physical systems via graph neural networks.
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OutlierDetectionNetworks.jl7Neural-Network Outlier Detection Algorithms for Julia
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MOTIFs.jl7DNA Motif discovery that includes the discovery of flexible (long or gapped) motifs.
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CEEDesigns.jl7A decision-making framework for the cost-efficient design of experiments, balancing the value of acquired experimental evidence and incurred costs.
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MLJParticleSwarmOptimization.jl7-
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TrackedDistributions.jl7-
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GlobalApproximationValueIteration.jl6-
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MLJEnsembles.jl6-
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GumbelSoftmax.jl6Julia implementation of the Gumbel-Softmax reparametrization trick compatible with Zygote and ForwardDiff
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Recommenders.jl6-
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IndependentHypothesisWeighting.jl6Independent Hypothesis Weighting for multiple testing with side-information in Julia
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JetPackWaveFD.jl6Jet operator pack for seismic modeling dependent on WaveFD.jl. Part of the COFII framework.
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